My ongoing fieldwork in a data-driven startup, referred to as Sage (a real company, but not its real name due to confidentiality requirements), suggests that technological solutions are not nearly as sophisticated as many assume — and are not going to replace human data entry any time soon.

For nearly two years, I’ve been studying the evolution of Sage’s hiring practices and jobs.

Sage’s initial plan was to develop and use AI to produce data it would sell to clients as part of its broader services. In the meantime, Sage asked its analysts to collect and enter that data manually. But when Sage ran a pilot project with an AI consulting firm, they discovered that AI would produce, at most, five per cent of the data that they were collecting manually, and at a substantially higher price.

They couldn’t afford the AI. As a result, they shifted their data-collection strategy from AI to human intelligence. Recognising that analysts were too expensive and would be too dissatisfied doing this work exclusively, Sage hired dedicated data entry operators in a satellite office to do much of the work.

Technology doesn’t always work

This type of scenario is not rare. Technology doesn’t always work as expected, and has varied effects across different jobs and organizations. The failings of technology, however, offer only a partial explanation of why manual data entry still exists as a task, and could for quite some time. To understand more, we need to consider tasks in a broader context.

This broader context, and the relationships within it, makes it difficult for any task to be eliminated altogether but also means that a single despised task does not always mean an entirely despised job.

At Sage, the very rote task of entering data was almost inseparable from the act of collecting data. While some of the data could be found easily in annual reports, for much of the rest, the analysts, and then the data entry operators, had to search the internet for additional information. Once they found this information, they then had to enter it into a database.

It would make no sense and would be virtually impossible to automate the data entry part of this task.

This highlights that not all data entry work is created equal, and not all data entry jobs are the same. As a result, attitudes about data entry are much more complex than the recent survey suggests.

False expectations

The Sage analysts did despise the data entry work, but not only because of the nature of the task itself. Expectations shaped their attitudes. When they were hired, many of them had expectations that they would be doing what they called analyst work — things like creating reports from data, writing content and interacting with clients.

Some of them had initially applied for consulting jobs that were to be made of up of the aforementioned responsibilities. They were expecting work that was more glamorous, more fulfilling. In this context, it’s not surprising that they considered data entry drudgery and thought it was beneath them.

The data entry operators, on the other hand, were hired with expectations that they would be doing what the title of the job implied — data entry. Unlike the analysts, some of them reported being pleasantly surprised by the job and the amount of thinking and judgment it involved.

Data entry operators promoted

The story at Sage is far from complete. I continue to watch as the tasks and roles evolve there. A recent strategy pivot at the company has meant that data collection became less central to the firm’s goals.

With this pivot, the role of the analysts has evolved to include much more interaction with the company’s developers in creating products for the clients and doing more to produce content.

The data entry operator job, however, is largely unchanged. People do come and go from it, but some of the data entry people have been promoted to analyst positions, suggesting that the dreaded task may be a pathway to less dreaded work.